Project 6 - AfterGlow Cloud

Project Overview:
This project aims to bring AfterGlow, an existing visualization tool to the Web (currently a command-line based tool). The project would enable AfterGlow as a service where in users can upload data and visualize their uploaded
data as graphs on-the-fly; while having the ability to control the output and its rendering options.

Tasks after this week are pending review and further discussion; to be updated.

Project Deliverables:
This project will deliver a cloud service that lets users visualize data as a link graph. The service will leverage a Web application based on Django; enabling the objectives listed above. Upon successful release of the first version (by July second week) some additional add-ons will be developed to the service.

Users can choose predefined expressions (which contain the expressions saved by other users) with a description.

App administrators get an email notifying them of an expression being saved (to double check if nothing malformed has been input).

Planned for the next week:

Integrate with Loggly.com's API using oAuth and let users parse/render their logs from Loggly.

Aug 13th:

Completed this weeks:

Integrated with Loggly.com as a data source for AfterGlow. User can now access their logs uploaded on their Loggly account (using oAuth for granting access) and can then have the data parsed/rendered as a graph.

Added more explicit error messages when a user inputs a malformed input.

Planned for the next week:

Add a gallery (opt-in) so that users can submit their graphs.

Deploy the application

Documentation and cleanup for a release

Aug 19th:

Completed this weeks:

Added a gallery - Users can now submit their rendered graphs (if they want) to a public gallery; with the details of their graph for other users to see.

Deployed the application on Apache using mod_wsgi

Settings/configurations chosen by a user to render their graphs are remembered, so that they can choose their "Last used settings" when attempting to render again.

Added feature: Rendering filter for GraphViz - users can now specify whether to use neato/dot/sfdp to render ther graphs.

Code cleanup and refactor throughout the codebase. Added documentation in the code-base and committed a new README for a fresh install of the application. This is the second release.